Brokers must adapt to artificial intelligence

As artificial intelligence becomes more embedded in the day-to-day business of real estate, industry leaders are tasked with evaluating how to implement new technology effectively, according to the report.

Rajeev Sajja, Bright MLS‘ first-ever chief AI and product officer, said the key issue is whether companies are preparing their data infrastructure to have AI help at the highest level.

The companies that prepare their data effectively are the ones that will succeed, Sajja believes, so AI can be a true intelligence layer, rather than just a one-off solution.

Sajja was joined by Emily Girard, CEO of Austin Board of Realtors and Unlock MLS, and Laura Ellis, recently promoted to chief revenue officer at Baird & Warner.

Ellis said there are “three distinct data groups” that brokerages can’t afford to give up to maintain their relevance in the transaction: consumer behavior, agent and broker coaching systems, and data flow within a firm’s ancillary services.

The most important thing agents can do for consumers is create as friction-free of a process as possible, Ellis added, noting that consumers don’t have an issue with paying commissions, but rather with what they get for that investment, which can impact the overall housing sales.

Girard emphasized the importance of data governance, saying brokers need to think critically about their relationship with vendors and what parts they actually own.

Brokerages need to have a better relationship with their data, Sajja agreed, knowing where their data is going, getting value from it, and who’s building intelligence on top of that.

Sajja stated that the industry hasn’t given enough thought to what it would look like if AI agents were to talk to other AI agents.

The industry must revisit its infrastructure and think about what the right guardrails are for this new era, a process that will need everyone’s help, Girard said.

Ellis said AI can handle some transaction management and lead generation tasks, but brokerages cannot outsource their agent coaching or productivity systems, similar to how software solutions are changing the way publishers monetize.

Brokerages should create an environment where the most highly productive agents can do as much business as they possibly want because the processes that support them become easier to navigate, Ellis added.

Sajja advised brokerages to have an enterprise agentic AI platform that helps build, govern, and deploy AI agents to automate the ordinary so agents and brokers can personalize the extraordinary, which are their client relationships.

Ellis advised building a system that works together, rather than just a list of tools, to avoid market fragmentation.

Preparing for an AI-Powered World

According to the report, retooling legacy systems, understanding data ownership, and knowing what to outsource will be key to operating in an AI-powered world.

This requires a deep understanding of data governance and the ability to think critically about vendor relationships and data ownership.

By doing so, brokerages can create a friction-free process for consumers and stay relevant in the transaction.

Data Governance and AI

Girard emphasized the importance of data governance in the AI era, saying it’s essential to have clarity around data ownership and vendor relationships.

This includes understanding what data is being collected, how it’s being used, and who has access to it, which they must manage effectively.

By having a clear understanding of data governance, they can ensure that their AI systems are working effectively and efficiently.